Experimental Studies of Low-field Landau Quantization in Two-dimensional Electron Systems in GaAs/AlGaAs Heterostructures

By applying a magnetic field perpendicular to GaAs/AlGaAs two-dimensional electron systems, we study the low-field Landau quantization when the thermal damping is reduced with decreasing the temperature. Magneto-oscillations following Shubnikov-de Haas (SdH) formula are observed even when their amplitudes are so large that the deviation to such a formula is expected. Our experimental results show the importance of the positive magneto-resistance to the extension of SdH formula under the damping induced by the disorder.Comment: 9 pages, 3 figure

Capture and inception of bubbles near line vortices

Motivated by the need to predict vortex cavitation inception, a study has been conducted to investigate bubble capture by a concentrated line vortex of core size rcrc and circulation Γ0Γ0 under noncavitating and cavitating conditions. Direct numerical simulations that solve simultaneously for the two phase flow field, as well as a simpler one-way coupled point-particle-tracking model (PTM) were used to investigate the capture process. The capture times were compared to experimental observations. It was found that the point-particle-tracking model can successfully predict the capture of noncavitating small nuclei by a line vortex released far from the vortex axis. The nucleus grows very slowly during capture until the late stages of the process, where bubble/vortex interaction and bubble deformation become important. Consequently, PTM can be used to study the capture of cavitating nuclei by dividing the process into the noncavitating capture of the nucleus, and then the growth of the nucleus in the low-pressure core region. Bubble growth and deformation act to speed up the capture process.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/87832/2/022105_1.pd

Resting-state magnetoencephalographic oscillatory connectivity to identify patients with chronic migraine using machine learning

To identify and validate the neural signatures of resting-state oscillatory connectivity for chronic migraine (CM), we used machine learning techniques to classify patients with CM from healthy controls (HC) and patients with other pain disorders. The cross-sectional study obtained resting-state magnetoencephalographic data from 240 participants (70 HC, 100 CM, 35 episodic migraine [EM], and 35 fibromyalgia [FM]). Source-based oscillatory connectivity of relevant cortical regions was calculated to determine intrinsic connectivity at 1–40 Hz. A classification model that employed a support vector machine was developed using the magnetoencephalographic data to assess the reliability and generalizability of CM identification. In the findings, the discriminative features that differentiate CM from HC were principally observed from the functional interactions between salience, sensorimotor, and part of the default mode networks. The classification model with these features exhibited excellent performance in distinguishing patients with CM from HC (accuracy ≥ 86.8%, area under the curve (AUC) ≥ 0.9) and from those with EM (accuracy: 94.5%, AUC: 0.96). The model also achieved high performance (accuracy: 89.1%, AUC: 0.91) in classifying CM from other pain disorders (FM in this study). These resting-state magnetoencephalographic electrophysiological features yield oscillatory connectivity to identify patients with CM from those with a different type of migraine and pain disorder, with adequate reliability and generalizability

Is mindfulness Buddhist? (and why it matters).

Modern exponents of mindfulness meditation promote the therapeutic effects of "bare attention"--a sort of non-judgmental, non-discursive attending to the moment-to-moment flow of consciousness. This approach to Buddhist meditation can be traced to Burmese Buddhist reform movements of the first half of the 20th century, and is arguably at odds with more traditional Theravāda Buddhist doctrine and meditative practices. But the cultivation of present-centered awareness is not without precedent in Buddhist history; similar innovations arose in medieval Chinese Zen (Chan) and Tibetan Dzogchen. These movements have several things in common. In each case the reforms were, in part, attempts to render Buddhist practice and insight accessible to laypersons unfamiliar with Buddhist philosophy and/or unwilling to adopt a renunciatory lifestyle. In addition, these movements all promised astonishingly quick results. And finally, the innovations in practice were met with suspicion and criticism from traditional Buddhist quarters. Those interested in the therapeutic effects of mindfulness and bare attention are often not aware of the existence, much less the content, of the controversies surrounding these practices in Asian Buddhist history

Channelling optics for high quality imaging of sensory hair

A long distance microscope (LDM) is extended by a lens and aperture array. This newly formed channelling LDM is superior in high quality, high-speed imaging of large field of views (FOV). It allows imaging the same FOV like a conventional LDM, but at improved magnification. The optical design is evaluated by calculations with the ray tracing code ZEMAX. High-speed imaging of a 2 × 2 mm(2) FOV is realized at 3.000 frames per second and 1 μm per pixel image resolution. In combination with flow sensitive hair the optics forms a wall shear stress sensor. The optics images the direct vicinity of twenty-one flow sensitive hair distributed in a quadratic array. The hair consists of identical micro-pillars that are 20 μm in diameter, 390 μm in length and made from polydimethylsiloxane (PDMS). Sensor validation is conducted in the transition region of a wall jet in air. The wall shear stress is calculated from optically measured micro-pillar tip deflections. 2D wall shear stress distributions are obtained with currently highest spatiotemporal resolution. The footprint of coherent vortical structures far away from the wall is recovered in the Fourier spectrum of wall shear stress fluctuations. High energetic patterns of 2D wall shear stress distributions are identified by proper orthogonal decomposition (POD)

Explainable AI (XAI) Applied in Machine Learning for Pain Modeling: A Review

Pain is a complex term that describes various sensations that create discomfort in various ways or types inside the human body. Generally, pain has consequences that range from mild to severe in different organs of the body and will depend on the way it is caused, which could be an injury, illness or medical procedures including testing, surgeries or therapies, etc. With recent advances in artificial-intelligence (AI) systems associated in biomedical and healthcare settings, the contiguity of physician, clinician and patient has shortened. AI, however, has more scope to interpret the pain associated in patients with various conditions by using any physiological or behavioral changes. Facial expressions are considered to give much information that relates with emotions and pain, so clinicians consider these changes with high importance for assessing pain. This has been achieved in recent times with different machine-learning and deep-learning models. To accentuate the future scope and importance of AI in medical field, this study reviews the explainable AI (XAI) as increased attention is given to an automatic assessment of pain. This review discusses how these approaches are applied for different pain types.This research was funded by Ministry of Science and Technology (MOST) of Taiwan, grant number: MOST 110-2221-E-155-004-MY2

Rapid intensification of Typhoon Hato (2017) over shallow water

© The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Pun, I., Chan, J. C. L., Lin, I., Chan, K. T. E., Price, J. F., Ko, D. S., Lien, C., Wu, Y., & Huang, H. Rapid intensification of Typhoon Hato (2017) over shallow water. Sustainability, 11(13), (2019): 3709, doi:10.3390/su11133709.On 23 August, 2017, Typhoon Hato rapidly intensified by 10 kt within 3 h just prior to landfall in the city of Macau along the South China coast. Hato’s surface winds in excess of 50 m s−1 devastated the city, causing unprecedented damage and social impact. This study reveals that anomalously warm ocean conditions in the nearshore shallow water (depth < 30 m) likely played a key role in Hato’s fast intensification. In particular, cooling of the sea surface temperature (SST) generated by Hato at the critical landfall point was estimated to be only 0.1–0.5 °C. The results from both a simple ocean mixing scheme and full dynamical ocean model indicate that SST cooling was minimized in the shallow coastal waters due to a lack of cool water at depth. Given the nearly invariant SST in the coastal waters, we estimate a large amount of heat flux, i.e., 1.9k W m−2, during the landfall period. Experiments indicate that in the absence of shallow bathymetry, and thus, if nominal cool water had been available for vertical mixing, the SST cooling would have been enhanced from 0.1 °C to 1.4 °C, and sea to air heat flux reduced by about a quarter. Numerical simulations with an atmospheric model suggest that the intensity of Hato was very sensitive to air-sea heat flux in the coastal region, indicating the critical importance of coastal ocean hydrography.The work of I.-F.P. is supported by Taiwan’s Ministry of Science and Technology Grant MOST 107-2111-M-008-001-MY3. The work of J.C.L.C. is supported by the Research Grants Council of Hong Kong Grant E-CityU101/16. The work of I.-I.L. is supported by Taiwan’s Ministry of Science and Technology (MOST 106-2111-M-002-011-MY3, MOST 108-2111-M-002-014-MY2). The work of K.T.F.C. is jointly supported by the National Natural Science Foundation of China (41775097), and the National Natural Science Foundation of China and Macau Science and Technology Development Joint Fund (NSFC-FDCT), China and Macau (41861164027)

Collapsing lattice animals and lattice trees in two dimensions

We present high statistics simulations of weighted lattice bond animals and lattice trees on the square lattice, with fugacities for each non-bonded contact and for each bond between two neighbouring monomers. The simulations are performed using a newly developed sequential sampling method with resampling, very similar to the pruned-enriched Rosenbluth method (PERM) used for linear chain polymers. We determine with high precision the line of second order transitions from an extended to a collapsed phase in the resulting 2-dimensional phase diagram. This line includes critical bond percolation as a multicritical point, and we verify that this point divides the line into two different universality classes. One of them corresponds to the collapse driven by contacts and includes the collapse of (weakly embeddable) trees, but the other is {\it not yet} bond driven and does not contain the Derrida-Herrmann model as special point. Instead it ends at a multicritical point $P^*$ where a transition line between two collapsed phases (one bond-driven and the other contact-driven) sparks off. The Derrida-Herrmann model is representative for the bond driven collapse, which then forms the fourth universality class on the transition line (collapsing trees, critical percolation, intermediate regime, and Derrida-Herrmann). We obtain very precise estimates for all critical exponents for collapsing trees. It is already harder to estimate the critical exponents for the intermediate regime. Finally, it is very difficult to obtain with our method good estimates of the critical parameters of the Derrida-Herrmann universality class. As regards the bond-driven to contact-driven transition in the collapsed phase, we have some evidence for its existence and rough location, but no precise estimates of critical exponents.Comment: 11 pages, 16 figures, 1 tabl

Constraints on background contributions from K+ Lambda electroproduction

Results for response functions for kaon electroproduction on the proton are presented. A tree-level hadrodynamical model is adopted and it is shown that some of the electroproduction response functions are particularly powerful with the eye on gaining control over the parameterization of the background diagrams. The existing data set for the p(e,e'K+)Lambda reaction appears to rule out the use of a g_{K+ Lambda p} coupling constant beyond the boundaries of softly broken SU(3) flavor symmetry. Also the use of soft hadronic form factors, which has been proposed as a valid alternative for a hadrodynamical description of the p(gamma,K+)Lambda data in the resonance region, seems to be disfavored by the magnitude of the measured p(e,e'K+)Lambda cross sections.Comment: Accepted for publication in PRC. Includes new data, additional paragraph and figur